M. Imran Hayee
, Professor, UMD-Electrical Engineering
Lane departure by a single vehicle on a curved road is a major safety risk. There are some in-vehicle lane departure warning systems available today which are either vision based or use GPS technology. Vision-based systems rely on image processing of pictures of road markings taken by cameras installed on front of the vehicle. These systems work reliably when road markings are clearly visible, a condition unlikely to be met during adverse weather and variable lighting scenarios. Similarly, there are some lane departure warning systems that use differential GPS receivers with centimeter level accuracy as well as high-resolution road maps. Such systems can work reliably in almost all weather conditions but are very costly to implement. An earlier project developed and successfully demonstrated a lane departure warning system that can also provide an advance curve speed warning using standard GPS receivers and commonly available low resolution mapping data. This system acquires trajectory of a moving vehicle in real time using standard GPS receiver and compares it with a reference direction of travel to detect lane departure. In the aforementioned project, the necessary reference direction of travel was provided by a low resolution map database commonly available in any navigation system. This new project proposes to develop and demonstrate a lane departure and advanced curve speed warning system using Dedicated Short Range Communication (DSRC)-based vehicle-to-vehicle (V2V) communication. The system will obtain the trajectory of a moving vehicle using standard GPS technology and compare it to the reference direction of travel obtained by the neighboring vehicles via DSRC-based V2V communication to calculate the lateral shift and detect lane departure. The system will be more efficient in comparison to the lane departure warning system developed earlier and will work with low market penetration levels of DSRC technology.
- Project number: 2019014
- Start date: 06/2018
- Project status: Active
- Research area: Transportation Safety and Traffic Flow